ALBERT

Description: The Surface Ocean CO2 Atlas (SOCAT) is a synthesis of quality-controlled fCO2 (fugacity of carbon dioxide) values for the global surface oceans and coastal seas with regular updates. Version 3 of SOCAT has 14.5 million fCO2 values from 3646 data sets covering the years 1957 to 2014. This latest version has an additional 4.4 million fCO2 values relative to version 2 and extends the record from 2011 to 2014. Version 3 also significantly increases the data availability for 2005 to 2013. SOCAT has an average of approximately 1.2 million surface water fCO2 values per year for the years 2006 to 2012. Quality and documentation of the data has improved. A new feature is the data set quality control (QC) flag of E for data from alternative sensors and platforms. The accuracy of surface water fCO2 has been defined for all data set QC flags. Automated range checking has been carried out for all data sets during their upload into SOCAT. The upgrade of the interactive Data Set Viewer (previously known as the Cruise Data Viewer) allows better interrogation of the SOCAT data collection and rapid creation of high-quality figures for scientific presentations. Automated data upload has been launched for version 4 and will enable more frequent SOCAT releases in the future. High-profile scientific applications of SOCAT include quantification of the ocean sink for atmospheric carbon dioxide and its long-term variation, detection of ocean acidification, as well as evaluation of coupled-climate and ocean-only biogeochemical models. Users of SOCAT data products are urged to acknowledge the contribution of data providers, as stated in the SOCAT Fair Data Use Statement. This ESSD (Earth System Science Data) "Living Data" publication documents the methods and data sets used for the assembly of this new version of the SOCAT data collection and compares these with those used for earlier versions of the data collection (Pfeil et al., 2013; Sabine et al., 2013; Bakker et al., 2014).

Description: The Surface Ocean CO2 Atlas (SOCAT) is a synthesis of quality-controlled fCO2 (fugacity of carbon dioxide) values for the global surface oceans and coastal seas with regular updates. Version 3 of SOCAT has 14.7 million fCO2 values from 3646 data sets covering the years 1957 to 2014. This latest version has an additional 4.6 million fCO2 values relative to version 2 and extends the record from 2011 to 2014. Version 3 also significantly increases the data availability for 2005 to 2013. SOCAT has an average of approximately 1.2 million surface water fCO2 values per year for the years 2006 to 2012. Quality and documentation of the data has improved. A new feature is the data set quality control (QC) flag of E for data from alternative sensors and platforms. The accuracy of surface water fCO2 has been defined for all data set QC flags. Automated range checking has been carried out for all data sets during their upload into SOCAT. The upgrade of the interactive Data Set Viewer (previously known as the Cruise Data Viewer) allows better interrogation of the SOCAT data collection and rapid creation of high-quality figures for scientific presentations. Automated data upload has been launched for version 4 and will enable more frequent SOCAT releases in the future. High-profile scientific applications of SOCAT include quantification of the ocean sink for atmospheric carbon dioxide and its long-term variation, detection of ocean acidification, as well as evaluation of coupled-climate and ocean-only biogeochemical models. Users of SOCAT data products are urged to acknowledge the contribution of data providers, as stated in the SOCAT Fair Data Use Statement. This ESSD (Earth System Science Data) "living data" publication documents the methods and data sets used for the assembly of this new version of the SOCAT data collection and compares these with those used for earlier versions of the data collection (Pfeil et al., 2013; Sabine et al., 2013; Bakker et al., 2014). Individual data set files, included in the synthesis product, can be downloaded here: doi:10.1594/PANGAEA.849770. The gridded products are available here: doi:10.3334/CDIAC/OTG.SOCAT_V3_GRID.

Description: The Global Ocean Data Analysis Project (GLODAP) is a synthesis effort providing regular compilations of surface to bottom ocean biogeochemical data, with an emphasis on seawater inorganic carbon chemistry and related variables determined through chemical analysis of water samples. This update of GLODAPv2, v2.2019, adds data from 116 cruises to the previous version, extending its coverage in time from 2013 to 2017, while also adding some data from prior years. GLODAPv2.2019 includes measurements from more than 1.1 million water samples from the global oceans collected on 840 cruises. The data for the 12 GLODAP core variables (salinity, oxygen, nitrate, silicate, phosphate, dissolved inorganic carbon, total alkalinity, pH, CFC-11, CFC-12, CFC-113, and CCl4) have undergone extensive quality control, especially systematic evaluation of bias. The data are available in two formats: (i) as submitted by the data originator but updated to WOCE exchange format and (ii) as a merged data product with adjustments applied to minimize bias. These adjustments were derived by comparing the data from the 116 new cruises with the data from the 724 quality-controlled cruises of the GLODAPv2 data product. They correct for errors related to measurement, calibration, and data handling practices, taking into account any known or likely time trends or variations. The compiled and adjusted data product is believed to be consistent to better than 0.005 in salinity, 1 % in oxygen, 2 % in nitrate, 2 % in silicate, 2 % in phosphate, 4 µmol kg−1 in dissolved inorganic carbon, 4 µmol kg−1 in total alkalinity, 0.01–0.02 in pH, and 5 % in the halogenated transient tracers. The compilation also includes data for several other variables, such as isotopic tracers. These were not subjected to bias comparison or adjustments. The original data, their documentation and DOI codes are available in the Ocean Carbon Data System of NOAA NCEI (https://www.nodc.noaa.gov/ocads/oceans/GLODAPv2_2019/, last access: 17 September 2019). This site also provides access to the merged data product, which is provided as a single global file and as four regional ones – the Arctic, Atlantic, Indian, and Pacific oceans – under https://doi.org/10.25921/xnme-wr20 (Olsen et al., 2019). The product files also include significant ancillary and approximated data. These were obtained by interpolation of, or calculation from, measured data. This paper documents the GLODAPv2.2019 methods and provides a broad overview of the secondary quality control procedures and results.

Description: The Global Ocean Data Analysis Project (GLODAP) is a synthesis effort providing regular compilations of surface to bottom ocean biogeochemical data, with an emphasis on seawater inorganic carbon 40 chemistry and related variables determined through chemical analysis of water samples. This update of GLODAPv2, v2.2019, adds data from 116 cruises to the previous version, extending its coverage in time from 2013 to 2017 while also adding some data from prior years. GLODAPv2.2019 includes measurements from more than 1.1 million water samples from the global oceans collected on 840 cruises. The data for the 12 GLODAP core variables (salinity, oxygen, nitrate, silicate, phosphate, dissolved inorganic carbon, total alkalinity, pH, CFC-11, CFC-12, CFC-113, and CCl4) have been subjected to extensive quality control, especially systematic evaluation of bias. The data are available in two formats: (i) as submitted by the data originator but updated to WOCE exchange format and (ii) as a merged data product with adjustments applied to minimize bias. These adjustments were derived by comparing the data from the 116 new cruises with the data from the 724 quality-controlled cruises of the GLODAPv2 data product. They correct for errors related to measurement, calibration, and data handling practices, taking into account any known or likely time trends or variations. The compiled and adjusted data product is believed to be consistent to better that 0.005 in salinity, 1 % in oxygen, 2 % in nitrate, 2 % in silicate, 2 % in phosphate, 4 μmol kg−1 in dissolved inorganic carbon, 4 μmol kg−1 in total alkalinity, 0.01 in pH, and 5 % in the halogenated transient tracers. The compilation also includes data for several other variables, such as isotopic tracers. These were not subjected to bias comparison or adjustments. The original data, their documentation and doi codes are available at the Ocean Carbon Data System of NOAA/NCEI (https://www.nodc.noaa.gov/ocads/oceans/GLODAPv2_2019/). This site also provides access to the merged data product, which is provided as a single global file or as four regional ones – the Arctic, Atlantic, Indian, and Pacific oceans – under the doi: https://doi.org/10.25921/xnme-wr20 (Olsen et al., 2019). The product files also include significant ancillary and approximated data. These were obtained by interpolation of, or calculation from, measured data. This paper documents the GLODAPv2.2019 methods and provides a broad overview of the secondary quality control results.

Description: The purpose of task 1 in WP7 in AtlantOS project is to harmonize data exchange and data processing procedures for the EOVs that are acquired by multiple networks. In this framework, the present report [D7.2] establishes recommendations for automatic quality control procedures in Near RT (a few hours to several days) for the core of 7 EOVs (measured by more than one of Networks involved in AtlantOS): • Physics : temperature (T), Salinity (T), Current for surface and subsurface and Sea level • Biogeochemistry : Oxygen (O2), Chlorophyll-A, Nitrate (NO3) and Carbon (pCO2) for surface and subsurface The recommendations have been compiled by experts on those EOVs and validated by the Networks acquiring those EOVs in NRT (link with WP2, WP3 and WP4). These recommendations will evolve with time under the EuroGOOS DATAMEQ working group umbrella (http://eurogoos.eu/data-management-exchange-quality-working-group-data-meq/) and benefit from scientific progress made by the observing Networks via the Task teams established within EuroGOOS (http://eurogoos.eu/task-teams/) These recommendations do not address the delayed mode quality control proceeses.

Description: Well-founded data management systems are of vital importance for ocean observing systems as they ensure that essential data are not only collected but also retained and made accessible for analysis and application by current and future users. Effective data management requires collaboration across activities including observations, metadata and data assembly, quality assurance and control (QA\QC), and data publication that enables local and interoperable discovery and access and secures archiving that guarantees long-term preservation. To achieve this, data should be findable, accessible, interoperable, and reusable (FAIR). Here, we outline how these principles apply to ocean data and illustrate them with a few examples. In recent decades, ocean data managers, in close collaboration with international organizations, have played an active role in the improvement of environmental data standardization, accessibility, and interoperability through different projects, enhancing access to observation data at all stages of the data life cycle and fostering the development of integrated services targeted to research, regulatory, and operational users. As ocean observing systems evolve and an increasing number of autonomous platforms and sensors are deployed, the volume and variety of data increase dramatically. For instance, there are more than 70 data catalogs that contain metadata records for the polar oceans, a situation that makes comprehensive data discovery beyond the capacity of most researchers. To better serve research, operational, and commercial users, more efficient turnaround of quality data in known formats and made available through Web services is necessary. In particular, automation of data workflows will be critical to reduce friction throughout the data value chain. Adhering to the FAIR principles with free, timely, and unrestricted access to ocean observation data is beneficial for the originators, has obvious benefits for users, and is an essential foundation for the development of new services made possible with big data technologies.

Description: The Global Ocean Data Analysis Project (GLODAP) is a synthesis effort providing regular compilations of surface to bottom ocean biogeochemical data, with an emphasis on seawater inorganic carbon chemistry and related variables determined through chemical analysis of water samples. This update of GLODAPv2, v2.2019, adds data from 116 cruises to the previous version, extending its coverage in time from 2013 to 2017, while also adding some data from prior years. GLODAPv2.2019 includes measurements from more than 1.1 million water samples from the global oceans collected on 840 cruises. The data for the 12 GLODAP core variables (salinity, oxygen, nitrate, silicate, phosphate, dissolved inorganic carbon, total alkalinity, pH, CFC-11, CFC-12, CFC-113, and CCl4) have undergone extensive quality control, especially systematic evaluation of bias. The data are available in two formats: (i) as submitted by the data originator but updated to WOCE exchange format and (ii) as a merged data product with adjustments applied to minimize bias. These adjustments were derived by comparing the data from the 116 new cruises with the data from the 724 quality-controlled cruises of the GLODAPv2 data product. They correct for errors related to measurement, calibration, and data handling practices, taking into account any known or likely time trends or variations. The compiled and adjusted data product is believed to be consistent to better than 0.005 in salinity, 1 % in oxygen, 2 % in nitrate, 2 % in silicate, 2 % in phosphate, 4 µmol kg−1 in dissolved inorganic carbon, 4 µmol kg−1 in total alkalinity, 0.01–0.02 in pH, and 5 % in the halogenated transient tracers. The compilation also includes data for several other variables, such as isotopic tracers. These were not subjected to bias comparison or adjustments.

Description: The European Research Infrastructure Consortium “Integrated Carbon Observation System” (ICOS) aims at delivering high quality greenhouse gas (GHG) observations and derived data products (e.g., regional GHG-flux maps) for constraining the GHG balance on a European level, on a sustained long-term basis. The marine domain (ICOS-Oceans) currently consists of 11 Ship of Opportunity lines (SOOP – Ship of Opportunity Program) and 10 Fixed Ocean Stations (FOSs) spread across European waters, including the North Atlantic and Arctic Oceans and the Barents, North, Baltic, and Mediterranean Seas. The stations operate in a harmonized and standardized way based on community-proven protocols and methods for ocean GHG observations, improving operational conformity as well as quality control and assurance of the data. This enables the network to focus on long term research into the marine carbon cycle and the anthropogenic carbon sink, while preparing the network to include other GHG fluxes. ICOS data are processed on a near real-time basis and will be published on the ICOS Carbon Portal (CP), allowing monthly estimates of CO2 air-sea exchange to be quantified for European waters. ICOS establishes transparent operational data management routines following the FAIR (Findable, Accessible, Interoperable, and Reusable) guiding principles allowing amongst others reproducibility, interoperability, and traceability. The ICOS-Oceans network is actively integrating with the atmospheric (e.g., improved atmospheric measurements onboard SOOP lines) and ecosystem (e.g., oceanic direct gas flux measurements) domains of ICOS, and utilizes techniques developed by the ICOS Central Facilities and the CP. There is a strong interaction with the international ocean carbon cycle community to enhance interoperability and harmonize data flow. The future vision of ICOS-Oceans includes ship-based ocean survey sections to obtain a three-dimensional understanding of marine carbon cycle processes and optimize the existing network design.